Reinforcement learning approach for job shop scheduling

Next-generation scheduling problem solver based on GNNs and Reinforcement Learning

This repository provides an OpenAI Gym-compatible environment for production scheduling tasks, designed to benchmark reinforcement learning agents in job shop and flow shop settings.

python-lekin: Flexible Supply Chain Planning and Scheduler

A Gymnasium Environment for the Job Shop Problem Using the Disjunctive Graph Approach.

⚙️ Effortless and efficient task scheduling tailored for production, built with numpy.

Implementation of a Job Shop Scheduling Problem solver based on Genetic Algorithms

Job Shop Scheduling Problem benchmark instances from http://jobshop.jjvh.nl/ and some utility functions to work with JSP instances.

Apply DQN to OR-Library ft-06 problem, which gets makespan 58.

Ths project provides visualisation for the Job Shop Scheduling Problem. This is focused on Gantt charts. The input date for the visualisation is inspired by plotly's Gantt chart api

Python repository to generate and solve job-shop scheduling problems, extract features, and build datasets, enabling neural network model training for makespan prediction.